Around this time, my coworkers were pushing GitHub Copilot within Visual Studio Code as a coding aid, particularly around then-new Claude Sonnet 4.5. For my data science work, Sonnet 4.5 in Copilot was not helpful and tended to create overly verbose Jupyter Notebooks so I was not impressed. However, in November, Google then released Nano Banana Pro which necessitated an immediate update to gemimg for compatibility with the model. After experimenting with Nano Banana Pro, I discovered that the model can create images with arbitrary grids (e.g. 2x2, 3x2) as an extremely practical workflow, so I quickly wrote a spec to implement support and also slice each subimage out of it to save individually. I knew this workflow is relatively simple-but-tedious to implement using Pillow shenanigans, so I felt safe enough to ask Copilot to Create a grid.py file that implements the Grid class as described in issue #15, and it did just that although with some errors in areas not mentioned in the spec (e.g. mixing row/column order) but they were easily fixed with more specific prompting. Even accounting for handling errors, that’s enough of a material productivity gain to be more optimistic of agent capabilities, but not nearly enough to become an AI hypester.
下载虎嗅APP，第一时间获取深度独到的商业科技资讯，连接更多创新人群与线下活动
。关于这个话题，一键获取谷歌浏览器下载提供了深入分析
Москалькова заявила о новых условиях Киева для возвращения россиян с территории Украины14:51
第二十五条 违反治安管理行为在六个月以内没有被公安机关发现的，不再处罚。
fewer and farther between.